The package xxl.core.math provides classes that issue mathematical topics. One core competence are applications based on nonparametrical statistical methods. This includes particularly kernel based estimators. These permit a higher order analysis of given data by providing complex statistical estimators, e.g. kernel based density estimators. These estimators are applicable for the selectivity estimation of queries and thus cover a main issue of query optimization in database management systems.
Since the processing of data streams becomes more important, there are also methods provided that build complex statistical estimators online fulfilling the one-pass paradigma and consuming constant ressources. Additionally more simple aggregates, that are online computable, are available, sometimes even equipped with running confidence intervals.
Besides these techniques, there are other mathematical topics adressed. For instance, classes realizing numerical integration and the computation of a cubic Bezier-Spline interpolate are available and ready-to-use.